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Andrew G. Argeros
Dedicated and driven current undergraduate student with a passion for statistical, analytical, and machine learning approaches to modern issues. Enjoys problem solving through data driven thinking and computational methods.
Skilled in applications of R, SQL, and Python. Avid presenter at national data science competitions and academic conferences. Looking to gain experience in the corporate sector and to further skills in machine learning at scale.
Education
B.S. Computational Data Science; B.B.A. Business Analytics; Minor in Economics
Hamline University
St. Paul, MN
2022 (exp.) - 2018
- Advisors: Dr. Stacie Bosley and Dr. Andy Rundquist
- President’s Scholarship Recipient & Heim Scholar
- NCAA Varsity Athlete: Men’s Tennis
High School Dipolma
Coon Rapids High School
Coon Rapids, MN
2018 - 2014
- Graduated with Honors
- Two time National AP Scholar with Distinction
Research & Teaching Experience
Teaching Assistant: QMBE 3740 - Data Mining
Hamline University
St. Paul, MN
Current - 09/2021
- Assisting Dr. Brett Devine in teaching 33 students concepts of data science and machine learning in R. Course covers topics such as data quality, supervised regression and classification, and unsupervised clustering and text mining.
Research Assistant to the Dean
Hamline University School of Business
St. Paul, MN
Current - 01/2020
- Hired in 2020 for ad hoc data science needs in the Hamline Business School. Responsibilites include working closely with Dean McCarthy, Support Staff, and Faculty to effectively manage and deploy analyics and data science projects.
- Student Analytics Director of DAC @ Hamline high school data analytics competition.
Research Assistant to Dr. Eric Hammer
Hamline University School of Business
St. Paul, MN
05/2020 - 01/2019
- Analyzed modifications to inputs of Hawk/Dove game theory model through use of agent based simulation modeling.
- Planned collaboration on a project studying cultures’ proverbs and “pop-culture” on voting behavior. Based on the work of Michalopoulos and Xue (2017) on the effects of folklore on rational voting theory.
Industry Experience
Data Science Intern
ExceleraRx LLC - Shields Health Solutions
Minneapolis, MN
Current - 02/2020
- Currently directing and implementing at-scale analytics and production grade machine learning systems affecting major health systems, pharmaceutical manufacturers, payers, and pharmacies in the realm of specialty pharmacy.
- Built machine learning systems to identify patients at risk for inadherence in subpopulations of metastatic breast cancer and hepatitis C patients. Currently in production at several national health systems.
- Built a production string matching system using Zero Shot Natural Language Processing to match raw prescription text to analyzable data using serverless computing systems.
Consultant Data Scientist
Economic Development Company of Lancaster County
Lancaster, PA
01/2021 - 10/2020
- Used advanced Natural Languange Processing (NLP) and Computer Vision (CV) methods to analyze real-estate trends within the county. Lead a research project to be presented to Lancaster developers and realtors.
- Developed a cohort of similar communities to Lancaster, PA using T-Distributed Stochastic Neighbor Embedding (T-SNE) and Density Based Stochastic Clustering (DBSCAN) on Census data.
Consultant Data Scientist
Minnesota Hospital Association
St. Paul, MN
02/2020 - 11/2019
- Analyzed workforce data on MHA’s members for the assocation’s annual workforce review.
- Presented analysis to statewide health system leaders.
Financial Planning & Analysis Intern
Northwestern Mutual
Minneapolis, MN
01/2020 - 09/2019
- Worked on a team of six to analyze, forecast, and manage the financial outlooks of more than two thousand clients across the country. Oversaw client investment processes from onboarding through investment and rebalancing.
- Used basic forecasting techniques (ARIMA, Exponential Smoothing, etc.) to show trends in portfolio growth, client uptake, and advisor put-through.
- Built a production invoicing system using R and Shiny to effectively manage the department’s billing and receivables.
Selected Data Science Projects
Compliance to Recommended Tuberculosis Screening Prior to Initiating Biologic Treatment Across a Network of Health System Specialty Pharmacies
Pharmacy Quality Alliance Annual Meeting and Conference
Virutal
06/2021
- Analyzed effects of date-verified screening for tuberculosis patients within the Excelera Network with respect to patient adherence and outcomes.
- Listed as acknowledgment due to lack of pharmaceutical degree.
March Madness
MinneMUDAC 2021
Virutal
03/2021
- Built a machine learning system based on bootstrapped random forests to accurately predict game outcomes in the 2021 NCAA Men’s Basketball Tournament. Coauthor Max Bolger.
- Finished in top 25% of participating teams both graduate and undergraduate.
- Bracket finished in 90th percentile of ESPN’s Tournament Challenge.
MLB Team Success: Offense vs. Defense
The Federal Reserve Bank of Minneapolis
Minneapolis, MN
11/2020
- Analyzed the importence of different statistics on predicting Win/Loss percentage and strategic paradigm shift in MLB. Coauthors Ryan Brauer and Jake Dujmovic.
- First Prize Winner at Minnesota Economic Association General Conference
Forecasting Soybean Futures: Prophet & VAR
MinneMUDAC 2019
Eden Prairie, MN
11/2019
- Accurately forecasted the price of three target soybean futures securities. Model comprised of an ensemble of Facebook Prophet and Vector Autoregression. Model Accuracy ~99.5%. Coauthors Lindsey Hawk and Lindsay Steiger.
- 2nd Place Overall & Analytical Acumen Award Winner
- Invited to present to industry leaders at FASTCON 2020
The Future of Renewable Energy in New York City
BAC @ MC 2019
New York City, NY
05/2019
- Optimized and analyzed a solution to convert half of New York state’s energy needs to renewable energy. Coauthors Shanoah Harren, Lindsay Steiger, and Leah Wenner.
- 4th Place Overall
Publications
Dermatology Landscape: Continued Growth Within the Excelera Network
ExceleraRx and ShieldsRx Blogs
N/A
03/2021
- Coauthor with Angela Ouyang
Predicting Inactivity in Oncology Patients: Machine Learning Classification in The Excelera Network
White Paper
N/A
06/2020